Design, feasibility, performance assessment and optimization of the technical and financial viability of potential renewable energy and energy efficiency projects
Notice bibliographique
Résumé
Until recently, renewable energy technologies (RETs) have been confronted with a huge up-front cost due to technologies in development. However, massive and global deployment of renewable energy systems has led to significant cost reductions and performance improvements and the hope is to see increasing uptake of RETs by African countries. Cameroon a central African country is heavily reliant on hydropower, which contributes an estimated 60% to the country’s total installed 1,400MW capacity in 2015. In addition, there is constants power failure due to the non-reliability of the electric grid and load shedding to meet increasing demand and or to relieve stress on the primary energy source when demand for electricity is greater than the primary power source can supply. However, climate change poses additional huge risk (large reservoirs and dams drying up) and to meet the increasing demand, Cameroon is being forced to seek alternative power sources. In January 2014, Cameroon welcomed its first 72MW solar photovoltaic plant as well as the construction of a 500MW solar photovoltaic park in Q3 of 2015 in the northern region of Cameroon. It is common practice that energy efficiency and energy conservation lead to environmental sustainability. “Energy security starts with energy efficiency and the most sustainable energy option or system is energy conservation”. While it is common practice that energy efficiency and energy conservation lead to environmental sustainability, the building envelope also plays a key role in energy usage, energy conservation and thermal comfort for the building occupants. The rate of infiltration/leakage rate detect the rate of energy usage and cost of using energy. Having a tide and well-constructed building envelope is a key factor and helps reduce/reconcile buildings gas and electricity consumption. RETScreen Expert is the most current version of the RETScreen software and was released to the public on September 19, 2016. The software allows for the comprehensive identification, assessment and optimization of technical and financial viability of potential renewable energy and energy efficiency projects; as well as the measurement and verification of the actual performance of facilities and the identification of energy savings/production opportunities [1-3]. This paper will demonstrate how the software can be use in the design, feasibility, performance assessment and optimization of technical and financial viability of potential renewable energy and energy efficiency projects related to photovoltaic, solar thermal, building envelope and the replacement of non/less-efficient electrical equipment with more efficient and cost effective lamps like LEDs and the installation of smart power bars with automatic shut off function for TV screens, to take care of phantom power in large scale hotels. This approach will further reduce electricity usage and help diversified the sources of energy for a country like Cameroon, which is often subjected to constant power failure and load shedding to either relieve the stress on a primary energy source when demand for electricity is greater than the primary power source can supply or to meet power supply during the critical seasons.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,004 | 0,004 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,001 |
| Méta-épidémiologie (sens large) | 0,000 | 0,001 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,001 | 0,001 |
| Communication savante | 0,003 | 0,002 |
| Science ouverte | 0,001 | 0,001 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,008 | 0,002 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».